ReviewBiomedicines2026
Bridging the Precision Gap in Rheumatoid Arthritis: Spatial Transcriptomics, Spatial Proteomics, and Artificial Intelligence in Precision Health.
Review in Biomedicines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Framework for Rheumatoid Arthritis Assessment Using Thermal Images Based on DnCNN-MLR Hybrid Algorithm and Joint Temperature Indexing.Sensors (Basel, Switzerland) · 2026Article
- Toward Precision Health in Autoimmunity and Immune-Related Adverse Events: The Autoantibody Reactome, Spatial Omics, and Multimodal Data Integration.Biomedicines · 2026Article
- Integrating Artificial Intelligence with Global Genomic Resources: A Narrative Review of Implications for Precision Medicine.Journal of multidisciplinary healthcare · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by complex immune cell associations and continuous joint damage. Personalized clinical assessment and treatment options for RA remain hindered by a precision gap due to an inability to precisely match current global treatment strategies to individual molecular and spatial disease profiles. Recent advances in spatial transcriptomics and proteomics offer unprecedented opportunities to map molecular heterogeneity and spatial heterogeneity within RA tissues by identifying immune microenvironments activated during the disease, thus enabling precise therapeutic targeting. These techniques address the precision gap in RA by identifying distinct pathogenic subpopulations and cellular niches, providing insights into the biomolecules that possess significant therapeutic responses and are involved in disease progression. This review synthesizes recent findings demonstrating how spatial omics technologies, including spatial transcriptomics and proteomics, together with artificial intelligence, are transforming precision rheumatology.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.